关键词: 碳排放权交易, 碳绩效, 低碳技术创新, SE-SBM模型, 双重差分模型

Abstract:     Carbon emission rights trading is an important environmental regulation tool for the state to encourage enterprises to reduce carbon emission and achieve green and low-carbon development. Carbon performance reflects the relationship between business development and carbon dioxide emissions, and it is an important indicator to measure the development of green and low-carbon economy. Based on the panel data of China′s listed companies from 2010 to 2019, this paper empirically analyzed the impact of carbon emission rights trading on corporate carbon performance and its mechanism by using the measurement methods of SE-SBM, multi-period PSM-DID and mediating effect model. The main conclusions are as follows: carbon emission rights trading significantly improves corporate carbon performance; carbon emission rights trading positively affects corporate carbon performance by promoting corporate low-carbon technology innovation; and there is heterogeneity in the effect of carbon emission rights trading, which has a more significant role in promoting source control-based low-carbon technology innovation and has a better long-term effect. Based on the above conclusions, this paper put forward the following suggestions. First, relevant authority should continue to improve the carbon emission rights trading system and promote enterprises′ low-carbon technology innovation, so as to improve their carbon performance. They should further improve the carbon emission rights trading price mechanism and market mechanism, promote enterprises′ low-carbon technology innovation through cost constraints and economic incentives, so that the emission reduction effect achieved by innovation can bring tangible environmental and economic benefits to enterprises. The carbon emission rights trading system should comply with other environmental and economic policies to encourage enterprises to carry out low-carbon technology innovation. On the one hand, low carbon technology innovation with source control can help enterprises reduce carbon emissions from the root while avoiding the recurrence of governance costs. Therefore, it is necessary to provide policy support to economic behaviors adopting such innovation. On the other hand, end-governance of low-carbon technology innovation is also an indispensable means for enterprises to carry out environmental governance. However, as it fails to contribute to the greening of enterprise production process and low-carbon product structure, it has not become the best choice for enterprises under the role of carbon emission rights trading system. Relevant policies should focus on making up for the disadvantage of terminal innovation in terms of economic benefits. For example, in terms of enterprise income tax, enterprises which intend to purchase equipment used to improve their waste treatment process, and the enterprise income tax payable in the current year should be offset according to a certain proportion of the investment amount. At the same time, the end of the green research and development expenses before tax deduction proportion should be increased. Enterprises are encouraged to further reduce carbon emissions at the end of production, and they should work together with source treatment technologies to improve their carbon performance and achieve high-quality development.This paper clarified the mechanism and influence path of carbon emission rights trading on corporate carbon performance, enriched and expanded the research perspective of carbon emission rights trading at the micro level, provided some empirical evidence for the construction of national carbon emission rights trading, provided some theoretical basis for enterprises to improve their carbon performance with the help of carbon emission rights trading, and also provided some beneficial reference for the realization of the dual goals of “carbon peaking and carbon neutrality”.

Key words: carbon emission rights trading, carbon performance, low carbon technology innovation, SE-SBM model, difference-in-differences (DID) model